The technical field of this invention is life cycle management. Current practice of life cycle management of critical components for high value assets such as aircraft and rotorcraft fall into three categories: damage tolerance, safe-life and fail-safe. Each of these methods requires reliable predictions of damage evolution behavior to enable practical application. When mission requirements change during service, uncertainties in model inputs are substantial, or damage behavior mechanisms are not well understood, for example for advanced materials such as composites, it is difficult to predict damage evolution behavior. These traditional methods for life cycle management provide limited value. Furthermore, even when such models capture a substantial portion of the relevant behavior, calculations of uncertainties in sufficient time to support interactive decisions by owners, maintainers and operators are often extremely time consuming.
A common part of the life cycle management methods is the use of Nondestructive evaluation (NDE) methods. NDE methods provide information about near-surface, and bulk material condition for flat and curved parts or components. These methods can include periodic inspections as well as usage monitoring with onboard diagnostics. This information is then used in a condition based maintenance or prognostic health management programs to extend the service life of a variety of systems, such as engines and aircraft.
NDE of legacy and new aircraft platforms, performed at the depot or in the field, have a goal to reduce sustainment costs while maintaining a high level of safety and operational readiness. While inspections of fatigue critical locations may be performed to try to assess the damage, such as the presence of cracks, these inspections are often difficult and costly. Even with embeddable sensors the data recording may not be continuous during flight, since it is often more practical to connect to such sensors periodically to record damage/condition data than to fly instrumentation on-board for continuous monitoring. Thus, damage state data from such sensors is often sparse to reduce the impact on aircraft availability and costs. Similarly, existing damage tolerance methods use predictive tools for crack growth to set NDE inspection intervals, to reduce premature component retirements. These damage tolerance methodologies assume an initial crack size, just below the detection threshold of available NDE methods. Inspection intervals are then set at a fraction of the time it takes for the assumed initial crack to reach this critical crack size.
There are a number of difficulties with the damage tolerance approach. One is the typically lengthy time required to run the models for predicting cracks growth. A second is the substantial variation in crack initiation and growth behavior, even at essentially identical features on components. This uncertainty can limit the usefulness of the predictive models. A third is rapid crack growth, inherent in many dynamic components, which begins before conventional NDE methods can provide reliable crack detection. Since this information is needed by the damage tolerance method, it again can limit the usefulness of the predictive models.
Advanced NDE sensors suitable for inspection or monitoring of difficult-to-access locations are flexible and conformable eddy current sensors. Examples of such conformable sensors are described, for example, by Goldfine (U.S. Pat. No. 5,453,689), Vernon (U.S. Pat. No. 5,278,498), Hedengren (U.S. Pat. No. 5,315,234) and Johnson (U.S. Pat. No. 5,047,719). These sensors permit characterization of bulk and surface material conditions. Characterization of bulk material condition includes (1) measurement of changes in material state, i.e., degradation/damage caused by fatigue damage, creep damage, thermal exposure, or plastic deformation; (2) assessment of residual stresses and applied loads; and (3) assessment of processing-related conditions, for example from aggressive grinding, shot peening, roll burnishing, thermal-spray coating, welding or heat treatment. It also includes measurements characterizing material, such as alloy type, and material states, such as porosity and temperature. Characterization of surface and near-surface conditions includes measurements of surface roughness, displacement or changes in relative position, coating thickness, temperature and coating condition. Each of these includes detection of electromagnetic property changes associated with either microstructural and/or compositional changes, or electronic structure (e.g., Fermi surface) or magnetic structure (e.g., domain orientation) changes, or with single or multiple cracks, cracks or stress variations in magnitude, orientation or distribution.
Conventional eddy-current sensing involves the excitation of a conducting winding, the primary, with an electric current source of prescribed frequency. This produces a time-varying magnetic field at the same frequency, which in turn is detected with a sensing winding, the secondary. The spatial distribution of the magnetic field and the field measured by the secondary is influenced by the proximity and physical properties (electrical conductivity and magnetic permeability) of nearby materials. When the sensor is intentionally placed in close proximity to a test material, the physical properties of the material can be deduced from measurements of the impedance between the primary and secondary windings. Traditionally, scanning of eddy-current sensors across the material surface is then used to detect flaws, such as cracks.